Obesity is a growing health care crisis in the US and around the world as more than two-thirds of US adults are overweight which has resulted in $147 billion dollars in 2008 in medical costs associated with obesity. The primary cause stems from poor dietary habits, lack of physical activity, and a lack of tools that accurately track and measure calorie intake and energy expenditures.
Conventional methods of measuring energy expenditures include direct calorimetry and indirect calorimetry but these conventional methods are very expensive, bulky, and uncomfortable for the users. Additionally, the conventional methods are impractical for continuous monitoring in free-living conditions as they require daily calibrations and professional interpretation and analysis of the data.
Conventional methods of estimating energy expenditures include estimations based on speed, physical activity, and heart rate. However, these conventional methods all require individual calibration and/or knowledge of individual/user parameters such as gender, age, weight, height, etc. Additionally, estimations using speed are inaccurate due to device variances, estimations using physical activity are inaccurate due to the inability to distinguish static exercise, and estimations using heart rate are challenging because it is difficult to continuously and accurately monitor the heart rate in free living conditions, and it further requires a cumbersome calibration procedure in order to customize to the individuals. Therefore, there is a strong need for a solution that overcomes the aforementioned issues. The present invention addresses such a need.